🤖AI Actions
Automatic decisions
The AI decision-making process within the SRC.ai platform is a sophisticated sequence that hinges on real-time data analysis and predictive algorithms to enhance the in-app experience. Here’s how the AI navigates decision-making:
Data Collection and Analysis: As users engage with the app, the AI agent begins by collecting a variety of data points from the Server Database, which includes the user’s primary NFT profile and their broader user profile. This data forms the foundation for understanding user behavior and preferences.
Game Rule Application: With the data in hand, the AI agent consults the Vector Database to look up relevant game rules based on the individual user information. This ensures that the decisions made are personalized and adhere to the gameplay structure designed in the SRC Game Design database.
Multilayer Prompts Processing: The AI then receives a series of prompts – User Prompts, Data Prompts, and Call Prompts. These are essentially queries or commands that consider multiple layers of context, including the user’s current in-game activity, historical data, and potential future actions.
Action Estimation: The AI uses the LLM (Language Model) to process these prompts and estimates the game parameters to decide the best course of action. This could involve anything from suggesting the user take a new route, to offering opportunities to earn more tokens, or advising on NFT upgrades.
API Call Execution: Once the AI has reasoned through the best next step, it executes the decision through API calls. This might mean automatically leveling up an NFT, applying upgrade points, or using items to enhance the user’s gameplay.
Adaptive Reasoning: The AI continuously learns from the user’s responses to these actions and the outcomes of its decisions, leading to a sophisticated reasoning process that becomes more tailored and effective over time.
In essence, the AI within the SRC.ai platform acts as a comprehensive decision-making engine that not only responds to user input but anticipates needs and strategizes the optimal path for user engagement and reward maximization. Through this intelligent automation, the app experience becomes not just seamless but also deeply engaging, as each user’s journey is uniquely crafted by the AI’s intricate decision-making process.
Actions include followings:
Analyze driving data
Stealth
Endurance
Leveling up
Repair
Suggestion of NFT purchase
Buy more NFT (Future)
You can SKIP reading rest of the sections; Attributees, Stealth, Endurance, Minting, Level up and Rarity.
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